This second part of a two-volume work contains 22 research articles on various aspects of computational earthquake physics. Coverage includes the promising earthquake forecasting model LURR (Load-Unload Response Ratio); pattern informatics and phase dynamics and their applications; computational algorithms, including continuum damage models and visualization and analysis of geophysical datasets; and assimilation of data.

The first of a two-part work, this volume focuses on microscopic simulation, scaling physics, dynamic rapture and wave propagation, earthquake generation, cycle and seismic pattern. Topics covered range from numerical and theoretical studies of crack propagation, developments in finite difference methods for modeling faults, long time scale simulation of interacting fault systems, and modeling of crustal deformation through to mantle convection.

These proceedings contain a selection of peer-reviewed papers presented at the International Symposium on Geodesy for Earthquake and Natural Hazards (GENAH), Matsushima, Japan, 22-26 July, 2014. The scientific sessions focused on monitoring temporal and spatial changes in Earth's lithosphere and atmosphere using geodetic satellite systems, high rate GNSS as well as high resolution imaging (InSAR, Lidar). Researchers in various fields of geodesy discussed the role of geodesy in disaster mitigation and how groups with different techniques can collaborate toward such a goal.

This is the first of two volumes devoted to earthquakes and multi-hazards around the Pacific Rim. The circum-Pacific seismic belt is home to roughly 80% of the world’s largest earthquakes, making it the ideal location for investigating earthquakes and related hazards such as tsunamis and landslides. Gathering 16 papers that cover a range of topics related to multi-hazards, the book is divided into three sections: earthquake physics, earthquake simulation and data assimilation, and multi-hazard assessment and earthquake forecasting models. The first section includes papers on laboratory-derived rheological parameters as well as seismic studies in the Gulf of California and China. In turn, the second section includes papers on improvements in earthquake simulators as well as the statistical methods used to evaluate their performance, automated methods for determining fault slip using near-field interferometric data, variabilities in earthquake stress drops in California, and the use of social media data to supplement physical sensor data when estimating local earthquake intensity. The final section includes a paper on probabilistic tsunami hazard assessment, several papers on time-dependent seismic hazard analysis around the Pacific Rim, and a paper on induced and triggered seismicity at the Geysers geothermal field in California. Rapid advances are being made in our understanding of multi-hazards, as well as the range of tools used to investigate them. This volume provides a representative cross-section of how state-of-the-art knowledge and tools are currently being applied to multi-hazards around the Pacific Rim. The material here should be of interest to scientists involved in all areas of multi-hazards, particularly seismic and tsunami hazards. In addition, it offers a valuable resource for students in the geosciences, covering a broad spectrum of topics related to hazard research.

The study of earthquakes is a multidisciplinary field, an amalgam of geodynamics, mathematics, engineering and more. The overriding commonality between them all is the presence of natural randomness. Stochastic studies (probability, stochastic processes and statistics) can be of different types, for example, the black box approach (one state), the white box approach (multi-state), the simulation of different aspects, and so on. This book has the advantage of bringing together a group of international authors, known for their earthquake-specific approaches, to cover a wide array of these myriad aspects. A variety of topics are presented, including statistical nonparametric and parametric methods, a multi-state system approach, earthquake simulators, post-seismic activity models, time series Markov models with regression, scaling properties and multifractal approaches, selfcorrecting models, the linked stress release model, Markovian arrival models, Poisson-based detection techniques, change point detection techniques on seismicity models, and, finally, semi-Markov models for earthquake forecasting.

Knowledge in its pure state is tacit in nature—difficult to formalize and communicate—but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.